Using categorical regression instead of a NOAEL to characterize a toxicologist´s judgment in noncancer risk assessment

Noncancer health risk assessment involves the evaluation of multiple types of toxic effects. For regulatory recommendations, such as the Reference Dose (RfD), the US Environmental Protection Agency (EPA) relies heavily on expert judgment. This toxicologic judgment mixes toxic impact with likelihood: what effects are adverse, which of these is critical, and which dose is the highest reliable NOAEL (No-Observed-Adverse-Effect Level). Uncertainty is indicated by qualitative statements of confidence. Statistical regression using ordered categories of overall toxicity is proposed as a superior alternative. Uncertainty and variability are represented by statistical models, all relevant data are used, not just the NOAEL for the critical effect, and health risk can be estimated at exposure levels above the RfD